--- title: Extreme Event Likelihoods with Guided Generative Models description: Guided diffusion models can be used to efficiently sample rare, high-impact climate events like tropical cyclones without requiring brute-force Monte Carlo... canonical: https://daily.dev/posts/extreme-event-likelihoods-with-guided-generative-models-dehtvusgr twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Extreme Event Likelihoods with Guided Generative Models | daily.dev og:description: Guided diffusion models can be used to efficiently sample rare, high-impact climate events like tropical cyclones without requiring brute-force Monte Carlo... og:url: https://daily.dev/posts/extreme-event-likelihoods-with-guided-generative-models-dehtvusgr og:image: https://api.daily.dev/og/posts/dEhtvuSGR.png og:image:alt: Extreme Event Likelihoods with Guided Generative Models og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Extreme Event Likelihoods with Guided Generative Models **[NVIDIA Developer](https://daily.dev/sources/nvidiadev)** · 7 min read · 0 upvotes · 0 comments ## Summary Guided diffusion models can be used to efficiently sample rare, high-impact climate events like tropical cyclones without requiring brute-force Monte Carlo runs. The key challenge is correcting for the oversampling bias introduced by guidance — solved here via an odds ratio between guided and unguided distributions, enabling importance sampling. Using NVIDIA's cBottle climate emulator and Earth2Studio, the workflow generates tropical cyclone atmospheric states near a specified location and computes log-odds ratios to estimate true event likelihoods. This approach reduced standard error by 25% compared to naive Monte Carlo sampling. The technique generalizes beyond climate to any domain where rare events dominate risk, including finance, aerospace, and materials science. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Generating scenarios for extreme events, without extreme data](https://daily.dev/posts/generating-scenarios-for-extreme-events-without-extreme-data-ip6jakjb9) · MIT News · 2 upvotes · 0 comments - [How to Unlock Local Detail in Coarse Climate Projections with NVIDIA Earth-2](https://daily.dev/posts/how-to-unlock-local-detail-in-coarse-climate-projections-with-nvidia-earth-2-ytb5osqdn) · NVIDIA Developer · 1 upvotes · 0 comments - [DeepMind’s hurricane breakthrough has surprised weather scientists](https://daily.dev/posts/deepmind-s-hurricane-breakthrough-has-surprised-weather-scientists-zcbbleayw) · Ars Technica · 25 upvotes · 5 comments - [Using Transformers to Forecast Incredibly Rare Solar Flares](https://daily.dev/posts/using-transformers-to-forecast-incredibly-rare-solar-flares-ndt15zbqy) · Towards Data Science · 2 upvotes · 0 comments --- Tags: [#nvidia](https://daily.dev/tags/nvidia), [#diffusion-models](https://daily.dev/tags/diffusion-models) [View this post on daily.dev](https://daily.dev/posts/extreme-event-likelihoods-with-guided-generative-models-dehtvusgr) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Extreme Event Likelihoods with Guided Generative Models","url":"https://daily.dev/posts/extreme-event-likelihoods-with-guided-generative-models-dehtvusgr","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/extreme-event-likelihoods-with-guided-generative-models-dehtvusgr"},"datePublished":"2026-07-13T15:01:52.367Z","dateModified":"2026-07-13T15:02:12.143Z","description":"Guided diffusion models can be used to efficiently sample rare, high-impact climate events like tropical cyclones without requiring brute-force Monte Carlo...","image":"https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/image1.gif","thumbnailUrl":"https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/image1.gif","isAccessibleForFree":true,"articleSection":"NVIDIA Developer","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"NVIDIA Developer","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/86e45aab42ba48ce83103d01b1119910","url":"https://daily.dev/sources/nvidiadev"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/extreme-event-likelihoods-with-guided-generative-models-dehtvusgr","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"nvidia,diffusion-models","timeRequired":"PT7M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"NVIDIA Developer","item":"https://daily.dev/sources/nvidiadev"},{"@type":"ListItem","position":3,"name":"Extreme Event Likelihoods with Guided Generative Models"}]} ```